Screen Recording → AI Analysis → Performance Report Generation
Automatically analyze recorded gameplay footage using AI to detect visual artifacts and performance issues, then generate comprehensive reports for development teams.
Workflow Steps
Loom
Record and upload gameplay sessions
Use Loom to record gameplay sessions focusing on areas where visual issues might occur (character faces, lighting effects, texture rendering). Set up automatic uploads to cloud storage with consistent naming conventions including game version and test scenario.
OpenAI API
Analyze video frames for visual artifacts
Use OpenAI's Vision API to analyze key frames from the recorded footage. Create prompts that specifically look for common visual issues: distorted faces, unrealistic lighting, texture problems, or 'AI-generated' looking artifacts. Process frames at regular intervals (every 2-3 seconds).
Google Sheets
Generate automated QA reports
Compile AI analysis results into structured Google Sheets reports with timestamps, issue descriptions, severity ratings, and frame screenshots. Include summary statistics on issue frequency and recommendations for development priorities.
Workflow Flow
Step 1
Loom
Record and upload gameplay sessions
Step 2
OpenAI API
Analyze video frames for visual artifacts
Step 3
Google Sheets
Generate automated QA reports
Why This Works
Leverages AI's ability to consistently identify visual artifacts that human testers might miss or inconsistently report, creating objective quality metrics.
Best For
Game studios needing to systematically identify visual quality issues in their games
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